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ICSH 2015: Smart Health pp 204–209Cite as

Stress Quantification Using a Wearable Device for Daily Feedback to Improve Stress Management

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9545))

Abstract

Stress is becoming a major problem in our society and most people do not know how to cope with it. We propose a novel approach to quantify the stress level using psychophysiological measures. Using an automatic stress detector that can be implemented in a mobile application, we managed to create an alternative to automatically detect stress using sensors from a wearable device, and once it is detected, a score is calculated for each one of the records. By identifying the stress during the day and giving a numeric value from biological signals to it, a visualization could be produced to facilitate the analysis information by users.

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Notes

  1. 1.

    The algorithm will be publish on a future work by the same authors.

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Acknowledgments

This work has been supported by Asociación Mexicana de Cultura A.C. and the Consejo Nacional of Ciencia and Tecnología of México (CONACyT).

Author information

Authors and Affiliations

  1. Usability and Interactive Systems Lab, Department of Computer Science, Instituto Tecnológico Autónomo de México, Mexico City, Mexico

    Jesus Garcia-Mancilla & Victor M. Gonzalez

Authors
  1. Jesus Garcia-Mancilla
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  2. Victor M. Gonzalez
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Corresponding author

Correspondence to Jesus Garcia-Mancilla .

Editor information

Editors and Affiliations

  1. Institute of Automation,Bldg.1004, Chinese Academy of Sciences, Beijing, China

    Xiaolong Zheng

  2. University of Arizona, Tucson, Arizona, USA

    Daniel Dajun Zeng

  3. University of Arizona, Phoenix, USA

    Hsinchun Chen

  4. Mayo Clinic, Scottsdale, USA

    Scott J. Leischow

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© 2016 Springer International Publishing Switzerland

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Garcia-Mancilla, J., Gonzalez, V.M. (2016). Stress Quantification Using a Wearable Device for Daily Feedback to Improve Stress Management. In: Zheng, X., Zeng, D., Chen, H., Leischow, S. (eds) Smart Health. ICSH 2015. Lecture Notes in Computer Science(), vol 9545. Springer, Cham. https://doi.org/10.1007/978-3-319-29175-8_19

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  • DOI: https://doi.org/10.1007/978-3-319-29175-8_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29174-1

  • Online ISBN: 978-3-319-29175-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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